My Blog@CACM post for June is Five Principles for Programming Languages for Learners. The five principles I identify are:
- Connect to what learners know
- Keep cognitive load low
- Be honest
- Be generative and productive
- Test, don’t trust
I wrote the essay in response to Idit Harel’s influential essay American schools are teaching our kids how to code all wrong. There were many responses to Idit’s essay, on social media and in other blogs. Much of the discussion focused on text programming languages vs. drag-and-drop, blocks-based languages, which I don’t think is the most critical distinction.
In this post, I respond to two of the suggestions that came up in some of these discussions. I use the five principles to review the suggestions in a kind of heuristic evaluation.
==is type-insensitive equality, and
===is type sensitive equality/equivalence. So,
"5"==5is true, but
"5"===5is false. Counting the number of
Baker Franke of Code.org is promoting the essay Coding snobs are not helping our children prepare for the future as a response to Idit’s essay. The essay is about the application-building tool, Ready. Media theorist Dough Rushkoff has also been promoting Ready, What happens when anyone can code? We’re about to find out.
I disagree with Rushkoff’s description of Ready, even in the title. As the first essay by David Bennahum (a “Ready Maker and Venture Partner) points out, it’s explicitly not about using a programming language.
Our efforts at Ready, a platform that enables kids to make games, apps, whatever they want, without knowing a computer language, are designed to offer a new approach to broadening access to code literacy.
Bennahum’s essay means to be provocative — and even insulting, especially to all the teachers, developers, and researchers who have been creating successful contextualized computing education:
In this new world, learning coding is about moving away from computer languages, syntax, and academic exercises towards real world connections: game design and building projects that tie into other subjects like science and social studies… This is the inverse of how computer science has been taught, as an impersonal, disconnected, abstracted, mathematical exercise.
I can see how Rushkoff could be confused. These two quotes from the Ready team seem contradictory. It’s not clear how Ready can be both about “learning coding” and “code literacy” while also allowing kids to make “without knowing a computer language.” There is no programming language in Ready. What is coding then? Is it just making stuff? I agree with Rushkoff’s concerns about Ready.
True, if people don’t have to code, they may never find out how this stuff really works. They will be limited to the programming possibilities offered by the makers of the platforms, through which they assemble ready-made components into applications and other digital experiences.
Let’s consider Ready against the five principles I propose.
- Connect to what learners know – the components of Ready are the icons and sliders and text areas of any app or game. That part is probably recognizable to children.
- Keep cognitive load low – Ready is all about dragging and dropping pieces to put them together. My guess is that the cognitive load is low.
- Be honest – Ready is not “real” in most sense of authenticity. Yes, students build things that look like apps or games, but that’s not what motivates all students. More of Betsy DiSalvo’s “Glitch” students preferred Python over Alice (see blog post). Alice looked better (which appealed to students interested in media), but students knew that Python was closer to how professional programmers worked. Authenticity in terms of practice matters to students. No professional programmer solely drags and drops components. Programmers use programming languages.
- Be generative and productive – Ready completely fails this goal. There is no language, no notation. There is no tool to think with. It’s an app/game builder without any affordances for thinking about mathematics, science, economics, ecology, or any other STEM discipline. There’s a physics engine, but it’s a black box (see Hmelo and Guzdial on black box vs glass box scaffolding) — you can’t see inside it, you can’t learn from it. They build “models” with Ready (see this neurobiology example), but I have a hard time seeing the science and mathematics in what they’re building.
- Test, don’t trust – Ready offers us promises and quotes from experts, but no data, no results from use with students.
Ready is likely successful at helping students to make apps and games. It’s likely a bad choice for learners. I don’t see affordances in Ready for computational literacy.